GCP Hadoop refers to the use of Apache Hadoop, an open-source framework for distributed storage and processing of large datasets, on the Google Cloud Platform (GCP). GCP provides a range of services and tools for running and managing Hadoop clusters in the cloud.

Here are some key components and services related to GCP Hadoop:

Google Cloud Storage (GCS):

GCS is an object storage service offered by GCP, and it can be used as the underlying storage for Hadoop. Hadoop clusters running on GCP can read data from and write data to GCS.

Cloud Dataproc:

Cloud Dataproc is a managed service on GCP that simplifies the deployment and management of Apache Hadoop and Apache Spark clusters. It automates tasks like cluster provisioning, configuration, and scaling. With Cloud Dataproc, you can create Hadoop clusters of various sizes and versions to process your data efficiently.

BigQuery:

BigQuery is a serverless, highly scalable data warehouse offered by GCP. It can be integrated with Hadoop clusters on GCP to enable data transfer between Hadoop and BigQuery. This allows you to perform complex data transformations and analysis using Hadoop, and then load the results into BigQuery for further exploration.

Cloud Storage Connector:

The Cloud Storage Connector is a Hadoop plugin that allows Hadoop clusters to directly access data stored in GCS. It provides high-performance data access and enables seamless integration between Hadoop and GCS.

GCP Marketplace:

GCP Marketplace provides a variety of pre-configured Hadoop distributions, such as Cloudera, Hortonworks, and MapR. These distributions can be deployed on GCP with ease, allowing you to choose the Hadoop distribution that best fits your needs.

By utilizing GCP’s infrastructure and services, you can leverage the scalability, reliability, and flexibility of the cloud for running Hadoop workloads. GCP’s integration with Hadoop enables you to process and analyze large datasets efficiently, making it a popular choice for big-data analytics and batch-processing tasks.